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Open PHACTS computational protocols for in silico target validation of cellular phenotypic screens: knowing the
D Digles1, B Zdrazil1, J-M Neefs2
1Department of Pharmaceutical Chemistry , University of Vienna , Pharmacoinformatics Research Group , Althanstraße 14 , 1090 Wien , Austria .
Abstract:
Phenotypic screening is in a renaissance phase and is expected by many academic and industry leaders to accelerate the discovery of new drugs for new biology. Given that phenotypic screening is per definition target agnostic, the emphasis of in silico and in vitro follow-up work is on the exploration of possible molecular mechanisms and efficacy targets underlying the biological processes interrogated by the phenotypic screening experiments. Herein, we present six exemplar computational protocols for the interpretation of cellular phenotypic screens based on the integration of compound, target, pathway, and disease data established by the IMI Open PHACTS project. The protocols annotate phenotypic hit lists and allow follow-up experiments and mechanistic conclusions. The annotations included are from ChEMBL, ChEBI, GO, WikiPathways and DisGeNET. Also provided are protocols which select from the IUPHAR/BPS Guide to PHARMACOLOGY interaction file selective compounds to probe potential targets and a correlation robot which systematically aims to identify an overlap of active compounds in both the phenotypic as well as any kinase assay. The protocols are applied to a phenotypic pre-lamin A/C splicing assay selected from the ChEMBL database to illustrate the process. The computational protocols make use of the Open PHACTS API and data and are built within the Pipeline Pilot and KNIME workflow tools.
Insights
This study introduces computational protocols to interpret cellular phenotypic screening results. These methods integrate compound, target, pathway, and disease data to accelerate drug discovery for novel biology.
Area of Science:
- Computational biology
- Drug discovery
- Bioinformatics
Background:
- Phenotypic screening is crucial for identifying drug candidates for novel biological targets.
- Interpreting phenotypic screening data requires target agnostic approaches to elucidate molecular mechanisms.
- Existing methods lack integrated computational tools for comprehensive phenotypic screen analysis.
Purpose of the Study:
- To present six computational protocols for interpreting cellular phenotypic screens.
- To enable annotation of phenotypic hit lists for follow-up experiments and mechanistic conclusions.
- To demonstrate the utility of the Open PHACTS platform and data integration.
Main Methods:
- Integration of compound, target, pathway, and disease data using the IMI Open PHACTS API.
- Development of protocols within Pipeline Pilot and KNIME workflow tools.
- Utilizing databases like ChEMBL, ChEBI, GO, WikiPathways, and DisGeNET for annotation.
- Implementation of protocols for target selection and correlation analysis between phenotypic and kinase assays.
Main Results:
- Successful annotation of phenotypic hit lists, facilitating mechanistic interpretation.
- Demonstration of protocols using a pre-lamin A/C splicing assay from ChEMBL.
- Identification of potential drug targets and mechanisms underlying phenotypic effects.
- Development of a correlation robot for identifying overlapping active compounds.
Conclusions:
- The presented computational protocols enhance the interpretation of phenotypic screening data.
- These tools accelerate drug discovery by providing mechanistic insights and facilitating follow-up studies.
- Integration of diverse biological data through Open PHACTS is key to unlocking phenotypic screening potential.
